Radiographic features of knee and hip osteoarthritis represent characteristics of an individual, in addition to severity of osteoarthritis.

OBJECTIVE

To evaluate to what extent radiographic features of knees and hips that are normally related to osteoarthritis (OA) represent characteristics of an individual in addition to OA severity.

METHODS

We studied a cohort of individuals (n = 1002) with very early signs of hip and knee OA, from the Cohort Hip and Cohort Knee (CHECK) study. Baseline radiographs were evaluated by digital analyses, using Holy's and Knee Images Digital Analysis (KIDA) software, providing distinct quantitative measures of radiographic OA features. In addition, conventional Kellgren and Lawrence (KL) grading was performed. Digital parameters were evaluated for correlations within participants between contralateral (left vs. right hip and left vs. right knee), ipsilateral (e.g. left hip vs. left knee), and diagonal joints (e.g. left hip vs. right knee). Analyses were performed separately for participants with KL grade 0-I and those with evident radiographic OA (KL grade II-III). Regression analyses determined whether demographic characteristics were related to radiographic features.

RESULTS

Correlations between digital parameters and KL grade were moderate, and within each KL grade large variation was found. Within participants strong correlations were found for digital parameters between joints in individuals with KL grade 0-I (R = 0.60-0.89), strongest for contralateral comparison, but no statistically significant correlations were found for participants with KL grade II-III. The demographic characteristics age, gender, height, and weight were, to a limited extent (R(2) = 0.01-0.20) but statistically significant, related to radiographic characteristics.

CONCLUSION

Using digital analyses of radiographic OA, strong correlations between joints within participants were found. These correlations diminished when OA became evident. This has implications for monitoring joint damage in (very) early OA with digital analyses.